Machine Learning Engineer

Role overview

An opportunity to design and ship production-grade AI applications for enterprise customers, working across the entire model lifecycle. The position sits at the intersection of research and engineering, with a strong emphasis on turning prototypes into reliable products that integrate cleanly into user-facing experiences. It suits someone who enjoys owning work from idea to deployment.

Responsibilities

- Build and deploy end-to-end AI-powered applications for enterprise use cases - Develop APIs that wrap ML models and integrate them into production products - Connect data pipelines, models, and services into cohesive user experiences - Partner with ML, data, and engineering teammates to ship robust systems - Contribute to architecture choices, tooling decisions, and engineering standards - Document systems and share knowledge to support long-term maintainability

Requirements

- BSc or higher in Computer Science, Machine Learning, Mathematics, or a related field - Strong Python skills; familiarity with CUDA or C++ is a plus - Experience with at least one major ML framework such as PyTorch, TensorFlow, or JAX - Solid software engineering habits including testing, code reviews, and CI/CD - Pragmatic, results-oriented mindset with the ability to own work end-to-end - Fluent English; German is a plus

Nice to have

- Experience with real-time, low-latency ML pipelines - Hands-on work with transformer architectures, agentic systems, or deep learning - Familiarity with AWS, Azure, or on-premise deployment patterns

Benefits and work setup

- Remote-first setup with flexible hours within a CET ±2 to ±3h window - Mentorship directly from C-level leaders - Budget allocated for personal development and certifications - Regular team offsites and retreats - Real ownership of cutting-edge AI projects from day one